Teaching bayesian reasoning: an evaluation of a classroom tutorial for medical students

Détails

ID Serval
serval:BIB_A38DF0D48585
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Teaching bayesian reasoning: an evaluation of a classroom tutorial for medical students
Périodique
Medical Teacher
Auteur(s)
Kurzenhäuser S., Hoffrage U.
ISSN
0142-159X
Statut éditorial
Publié
Date de publication
2002
Peer-reviewed
Oui
Volume
24
Numéro
5
Pages
516-521
Langue
anglais
Résumé
How likely is a diagnosis, given a particular medical test result? This probability can be determined by using Bayes's rule; however, previous research has shown that doctors often experience problems with Bayesian inferences. These findings illustrate the need to teach statistical reasoning in medical education. A new method of teaching Bayesian reasoning is representation learning: the key idea is to instruct medical students how to translate probability information into a representation that is easier to process, namely natural frequencies. This approach was implemented in a one-hour classroom tutorial to evaluate its effectiveness in this setting and compared with a traditional rule-learning approach. Evaluation took place two months after training by testing students' ability to correctly solve a Bayesian inference task with information represented as probabilities. While both approaches improved performance, almost three times as many students were able to profit from representation training as opposed to rule training.
Web of science
Création de la notice
24/02/2009 15:34
Dernière modification de la notice
03/03/2018 20:11
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